1,329
Views
1
CrossRef citations to date
0
Altmetric
Original

FFT Analysis of the X-ray Tube Voltage Waveforms of High-Frequency Generators for Radiographic Systems

, , , , &
Pages 810-814 | Accepted 02 Aug 2005, Published online: 09 Jul 2009
 

Abstract

Purpose: To present a novel method for analyzing the voltage waveform from high-frequency X-ray generators for radiographic systems.

Material and Methods: The output signal of the actual voltage across the tube of a high-frequency generator was measured using the built-in voltage sense taps that are used for voltage regulation feedback in X-ray generators. The output signal was stored in an analyzing recorder, and the waveforms were analyzed using FFT analysis. The FFT analysis of high-frequency generators consisted of obtaining the power spectrum, comparing the major frequency components in the tube voltage waveforms, and examining the intensity of each frequency component.

Results: FFT analysis enables an objective comparison of the complex tube voltage waveforms in high-frequency X-ray generators. FFT analysis detected the change in the X-ray tube voltage waveform that occurred when there were problems with the high-frequency generator.

Conclusion: High-frequency X-ray generators are becoming the universal choice for radiographic systems. The X-ray tube voltage and its waveform are important features of an X-ray generator, and quality assurance (QA) is important, too. As a tool for engineers involved in the design and development of X-ray generators, we can see that our methods (FFT analysis) might have some value as a means of describing generator performance under varying conditions. Furthermore, since the X-ray tube voltage waveform of a high-frequency generator is complex, FFT analysis may be useful for QA of the waveform.

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.